| import gradio as gr | |
| import numpy as np | |
| import librosa | |
| from scipy.io.wavfile import write | |
| # import the librosa library for converting a Mel spectrogram image to audio | |
| def mel_to_audio(mel_spectrogram): | |
| # convert the Mel spectrogram image to a grayscale image to avoid the string indices must be integers error | |
| # convert the Mel spectrogram image to audio using librosa | |
| # specify the data type of the output array to avoid the same_kind casting error | |
| audio = librosa.feature.inverse.mel_to_audio(mel_spectrogram, dtype=np.float64) | |
| # Save the audio to a file | |
| output = 'output.wav' | |
| sample = 44100 | |
| print (output) | |
| write(output, sample, audio.astype(np.float64)) | |
| return output | |
| # create the gradio app | |
| app = gr.Interface(mel_to_audio, "image", "audio") | |
| app.launch() |